%differant kinds of search
In many multi-agent system(MAS) agents are engaged in search.
There are various types of search that agents can perform.  Sometimes agents are require to find the shortest path to destination or to find the solution(opportunity) which will maximize/minimize their utility function.  However, in many situations in environments were the process of evaluating opportunity incurs a cost the agents are required to maximize the overall benefit, defined as the value of an opportunity eventually picked minus the costs accumulated during the search process. The searcher thus needs to consider, at each step of its search, the trade off between the possible marginal gain
from revealing the values of further opportunities and the cost associated with it (McMillan and Rothschild 1994).
For example, when searching for a product our goal to minimize the minimal price of the product plus the costs accumulated during the search sequence rather than just finding the store that offers the product for the minimal price.
%bounded rational search
While search theory is a rich research field, its focus is on the theoretical
aspects of the optimal search strategy and it does not address the non-optimality of search 
strategies used by people or rationally-bounded and satisficing agents.
For a variety of decision-making/search situations, it has been shown that people do not choose optimally or follow an optimal strategy.  Research in psychology and behavioral economics has revealed various sources of this suboptimal behavior, rooted in various characteristics of human cognition and decision-making \cite{blackhart2005individual}.   
The phenomena recurs also in agents that are designed by non-specialists in decision-making theory \cite{chalamish2008programming}.  
  
The term bounded rationality was coined by Herbert Simon, it means that the rationality of individuals
is limited by the information they have, the cognitive limitations of their minds, 
and the finite amount of time they have to make decisions.  
When it comes to search theory the effect of bounded rationality has not been researched.
In this thesis we focus on rationally-bounded and satisficing agents engaged in search.
In our research the main reason for the decision maker's bounded rationality is not because of the effect of complexity, rather because it is hard for people to understand the nature of the optimal solution.

%The research is experimental methodology
This thesis considers settings of MAS where each agent designed by a different programmer is not necessarily using the optimal search strategy but rather what its programmer believe to be best.
It tests experimentally two main research questions under such setting.  
The first question is as follows: given an environment of searchers that do not follow the optimal strategy how can we help this searchers without teaching/giving them the optimal strategy.  The method we used in this thesis in order to help the searchers was "`choice architecture"', which means by manipulating the opportunities that the searcher is facing we can cause her to perform like the optimal strategy.   
The second question is: giving an environment of searchers were not all the searchers follow the optimal strategy what is the value that the provider will need to set in order to maximize his average utility(NOT SURE IF ITS THE CORRECT TERM). 

% summary of what the thesis consist
  In the next section we provide the necessary theoretical background for search
theory, the optimal search solution for fully rational agents, detailed
description of the infrastructure developed for testing the research hypothesis and analysis of the agent's strategies. 
Then in chapter \ref{chapter3} we detail our restructuring approach and present heuristics, followed by a detailed experimental results for the restructuring decisions method.
In chapter \ref{chapter4} we explain and show results for restructuring an opportunity to maximize benefit.
Finally on chapters \ref{chapter5} and \ref{chapter6} we give a discussion and directions for future research.

Related work is incorporated in the chapter itself when ever applicable.
